Models-based Optimization Methods for the Specication of Fuzzy Inference Systems in Discrete EVent Simulation
- Paul-Antoine Bisgambiglia, Bastien Poggi, Céline Nicolai
- Corresponding Author
- Paul-Antoine Bisgambiglia
Available Online August 2011.
- https://doi.org/10.2991/eusflat.2011.6How to use a DOI?
- DEVS, Fuzzy Sets Theory, FIS, optimization models, iDEVS, DEVFIS
- Fuzzy Inference Systems (FIS) have the advantage of relying on the properties of Fuzzy Logic to represent imperfect information so gradually, and manipulate them from a linguistic description. This exibility of representation is more signicant for the study of complex systems. Our aims are to propose a formal approach for describing FIS as a Discrete Event System (DES), and to extend a DES in order to use the many advantages oered by FIS: exibility, easy implementation, robustness... In this paper, we present the extension of Discrete EVent system Specication (DEVS) formalism to represent FIS, and we propose a modular approach (DEVFIS) to use several optimization methods. We focus mainly on the used new aproach about using genetic algoritm in order to optimize the FIS.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Paul-Antoine Bisgambiglia AU - Bastien Poggi AU - Céline Nicolai PY - 2011/08 DA - 2011/08 TI - Models-based Optimization Methods for the Specication of Fuzzy Inference Systems in Discrete EVent Simulation BT - Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 957 EP - 964 SN - 1951-6851 UR - https://doi.org/10.2991/eusflat.2011.6 DO - https://doi.org/10.2991/eusflat.2011.6 ID - Bisgambiglia2011/08 ER -